code: def allreduce_ring(xs, devices, reduction_fn_string="SUM"):
      """Compute the reduction of all Tensors and put the result everywhere.
  
      Performance-optimized for a ring of devices.
  
      Args:
        xs: a list of n tf.Tensors
        devices: a list of strings
        reduction_fn_string: "SUM" or "MAX"
  
      Returns:
        a list of n Tensors
      Raises:
        ValueError: if devices is not a list of n strings
      """
      n = len(xs)
      if len(devices) != n:
          raise ValueError("devices must be a list of length len(xs)")
      if n == 1:
          return xs
      shape = xs[0].shape.as_list()
      # tf.logging.info("allreduce_ring shape = %s" % shape)
      size = None if None in shape else mtf.list_product(shape)
      if size is None or size < 1024 or size % n != 0:
          return allreduce_ring_single_shard(
              xs, devices, reduction_fn_string
          )
  
      def _circular_shift(l, n):
          n %= len(l)
          return l[-n:] + l[:-n]
  
      def _flatten_and_split(x):
          # tf.reshape treats [-1] as a special value denoting 1D flattening.
          return tf.split(tf.reshape(x, [-1]), n)
  
      def _concat_and_reshape(xs):
          return tf.reshape(tf.concat(xs, 0), shape)
  
      # [device, shard]
      x_split = mtf.parallel(devices, _flatten_and_split, xs)
      x_split_t = mtf.transpose_list_of_lists(x_split)
  
      y_split_t = []
      for shard in xrange(n):
          shard_xs = _circular_shift(x_split_t[shard], shard)
          shard_devices = _circular_shift(devices, shard)
          shard_ys = allreduce_ring_single_shard(
              shard_xs, shard_devices, reduction_fn_string
          )
          y_split_t.append(_circular_shift(shard_ys, -shard))
      y_split = mtf.transpose_list_of_lists(y_split_t)
      ys = mtf.parallel(devices, _concat_and_reshape, y_split)
      return ys
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import functools
  import os
  import random
  from mesh_tensorflow import ops_with_redefined_builtins
  from six.moves import xrange
  import tensorflow.compat.v1
label_desc: Use image node_id 2 for calling a global function with example usage: allreduce_ring(xs, devices, reduction_fn_string) and returns: ys, xs, allreduce_ring_single_shard, unknown, tf, tf